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Aerodynamic optimisation of wind farms using turbulence modelling

  • Andrew Barnes

Student thesis: Doctoral Thesis

Abstract

With the need for decarbonisation and more abundant energy sources becoming more immediate, it is necessary to explore and optimise the world’s energy generation. The three major sources for this goal are considered to be nuclear, solar, and wind energy, where wind is the more abundant energy source in the UK.Currently, HAWTs are the standard wind turbine type deployed worldwide, however evidence has demonstrated that VAWTs may be better suited to some major wind energy applications, namely wind farms and floating turbines. The more complex flow problem of VAWTs has slowed their development by requiring greater resources to conduct equivalent simulations.This thesis addresses how VAWT turbine and array designs are evaluated. It proposes greater standardisation of VAWT designs to maximise efficiency and comparability of research, the importance of field conditions in evaluating VAWTs, and a more refined CFD procedure to enable quicker accurate VAWT simulation.Through a review of the literature and simulation, an analysis of VAWT aerodynamic design and simulation procedure is conducted. Choice of array design is compared, the impact of CFD procedure on accuracy in different scenarios is evaluated, and the impact of Reynolds Numbers and Turbulence Intensity on VAWT power outputs and wakes, and on simulation accuracy, is analysed.Analysis of array design demonstrated a potential 80% improvement in VAWT power output from using the Truss array design. The Four-equation turbulence model called Transition SST offers the greatest accuracy for predicting individual VAWT wakes however this was not sufficient for array predictions. Both Reynolds Number and Turbulence Intensity have a significant effect on VAWT wakes and CFD accuracy so must be accounted for.
Date of Award10 May 2023
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsUniversity of Strathclyde
SupervisorNick Kelly (Supervisor) & Paul Gerard Tuohy (Supervisor)

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